mojtaba jamiati
Articles in Press, Accepted Manuscript, Available Online from 21 May 2021
Abstract
Abstract— Using DC micro-grid to connect more efficiently with DC output has increased. The sources are photovoltaic and energy storage systems. The conversion losses of the sources for supplying the loads are reduced compared to the AC micro-grid. This method aims at combining the above methods ...
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Abstract— Using DC micro-grid to connect more efficiently with DC output has increased. The sources are photovoltaic and energy storage systems. The conversion losses of the sources for supplying the loads are reduced compared to the AC micro-grid. This method aims at combining the above methods to achieve maximum use of Renewable Energy and Energy Storage and enhancing the efficiency of the grid by using the Active power Filter and applying the DC to DC converter to boost the conversion efficiency and load management with having island inputs and the way to manage the inputs in the state of load disturbance and exit of one of the island inputs from the circuit is rapid injection of energy stored into the grid in the quickest time and the coordinated control between grid and photovoltaic system and battery have been studied in MATLAB/SIMULINK software. The amount of simulation time will be considered 0.5 seconds and the amount of sunlight vary of until
Fatemeh Kiayi; Behnaz Gharekhanlou; Alireza Kashaninya
Articles in Press, Accepted Manuscript, Available Online from 21 May 2021
Abstract
Over the years, the design and implementation of fault-tolerant circuits have been one of the main concerns of the designers of electronic devices. Quantum Dot Cellular Automata (QCA) is a low-power, compact technology that is prone to various defects due to its small size. We can categorize these defects ...
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Over the years, the design and implementation of fault-tolerant circuits have been one of the main concerns of the designers of electronic devices. Quantum Dot Cellular Automata (QCA) is a low-power, compact technology that is prone to various defects due to its small size. We can categorize these defects into three main groups: operational defects, manufacturing defects, and clocking defects. Using redundant cells, fault-tolerant gates, or changing the structure of the gates can improve the overall fault-tolerance of the circuit in some cases. However, increasing the fault-tolerance would lead to an increase in the occupied area and the delay of the gates. Therefore, designing a gate based on intercellular interactions with a minimum number of cells and maximum efficiency, which is also fault-tolerant, is a challenging task. In this paper, we present a new tile-shaped design for XOR and XNOR gates that is robust to the Missing cell, Extra cell, and Rotated cell defects by 25%, 55%, and 25%, respectively. That is why we call these gates TFXOR and TFXNOR, respectively.
Hassan Majidi; M.-R Haghifam; Mahdi Emadaleslami
Articles in Press, Accepted Manuscript, Available Online from 12 July 2021
Abstract
In recent years, due to developments in the electricity industry, the use of smart meters has increased worldwide. Smart meters allow the collection of large amounts of microdata on power consumption. The data collected by smart meters can be used in various cases. Since the load duration curve is of ...
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In recent years, due to developments in the electricity industry, the use of smart meters has increased worldwide. Smart meters allow the collection of large amounts of microdata on power consumption. The data collected by smart meters can be used in various cases. Since the load duration curve is of great importance in the study of power systems in this paper, the purpose is to obtain the load duration curve of consumer groups using raw smart meter data. The data collected by smart meters reflects the behavior of subscribers, so by categorizing this data, the behavior of subscribers can be categorized, and thus the continuous load curve can be calculated. However, due to challenges such as being raw data collected from smart meters, the presence of anomalous data, and the presence of lost data, the data collected by smart meters need to be pre-processed and corrected. This paper presents an approach for pre-processing and modification of raw data received from smart meters and using them to calculate the load duration curve and other uses. First, the preprocessing and modification of smart meter data on two data sets collected from Alborz Power Distribution Company is done based on the presented method; Then these data are clustered based on the k-means clustering algorithm, and finally, load duration curve is obtained for each cluster.
Mahdi Emadaleslami
Articles in Press, Accepted Manuscript, Available Online from 12 July 2021
Abstract
Electricity utility have long sought to identify and reduce energy fraud as a significant part of non-technical losses (NTL). Generally, to determine customer’s honesty in consumption on-site inspection is vital. Since, inspecting all customers is expensive, utilities look for new ways to reduce ...
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Electricity utility have long sought to identify and reduce energy fraud as a significant part of non-technical losses (NTL). Generally, to determine customer’s honesty in consumption on-site inspection is vital. Since, inspecting all customers is expensive, utilities look for new ways to reduce inspection’s range to cases with a higher probability of fraud. One way to reduce the scope of inspection is to use machine learning (ML) algorithms to analysis consumption pattern. But, their performance is not satisfactory due to insufficiency of fraudulent customers. In this paper, a new two-stage ML-based model is presented to detect fraud in distribution network. . In the first stage, an Artificial Neural Network (ANN) is trained to model fraudulent customers, which is used to predict theft scenarios for normal consumers to handle data insufficiency. In the second stage, a Support Vector Machine (SVM) classifier is trained to distinguish normal and suspicious consumers. Assessment and comparison of the proposed algorithm to those of conventional models on a real data set with more than 5000 customers shows its high performance.
